Congenital Chagas disease: time to screen pregnant women?

The congenital transmission of Trypanosoma cruzi has gained epidemiological importance because it is partially responsible for the spread of Chagas disease worldwide. The feasibility of a cure when infected children are treated early makes the detection of congenital infection a valuable goal toward the control of the disease. Here, the authors review and discuss the findings of Bua et al., who quantified the parasitemia of infected women and their newborns by quantitative PCR. The authors demonstrate that the maternal parasite burden is directly related to the risk of neonatal infection. This study points out the importance of a quantitative screen for T. cruzi in pregnant women who live in, or have traveled to, endemic areas for improving the diagnosis of infected newborns and providing prompt treatment.

Comparison between frequency domain and time domain riser analysis

In the optimization or parametric analyses of risers, several configurations must be analyzed. It is laborious to perform time domain solutions for the dynamic analysis, since they are time-consuming tasks. So, frequency domain solutions appear to be a possible alternative, mainly in the early stages of a riser design. However, frequency domain analysis is linear and requires that nonlinear effects are treated. The aim of this paper is to present a possible way to treat some of these nonlinearities, using an iterative process together with an analytical correction, and compare the results of a frequency domain analysis with the those of a full nonlinear analysis. [DOI: 10.1115/1.4006149]

Rates of description of Phytoseiidae mite species (Acari: Mesostigmata): space, time and body size variations

This study aims to analyse the degree of completeness of world inventory of the mite family Phytoseiidae and the factors that might determine the process of species description. The world data set includes 2,122 valid species described from 1839 to 2010. Species accumulation curves were analysed. The effect of localisation (latitude ranges) and body size on the species description patterns over space and time was assessed. A low proportion of species seems remain to be described, but this trend could be explained by a critical reduction in the number of specialists dedicated to the study of those mites. In addition, this trend refers to the areas where phytoseiids have been well studied around the world, and it may change considerably if the study of these mites would be intensified in some areas. The number of newly described species is lower near the tropics, and their body size is also smaller. Differences in body size were noted between the three sub-families of Phytoseiidae, the highest mean body lengths of adult females being observed for Amblyseiinae, the most diverse family. In the future, collections would have certainly to take into consideration such conclusions for instance in using more adequate optical equipment especially for field collections. The decrease in the number of phytoseiid mite described was confirmed and the factors that could explain such a trend are discussed. Information for improving further inventories is provided and discussed, especially in relation to sampling localization and study methods.

Constraint-based analysis of gene interactions using restricted boolean networks and time-series data

Abstract Background A popular model for gene regulatory networks is the Boolean network model. In this paper, we propose an algorithm to perform an analysis of gene regulatory interactions using the Boolean network model and time-series data. Actually, the Boolean network is restricted in the sense that only a subset of all possible Boolean functions are considered. We explore some mathematical properties of the restricted Boolean networks in order to avoid the full search approach. The problem is modeled as a Constraint Satisfaction Problem (CSP) and CSP techniques are used to solve it. Results We applied the proposed algorithm in two data sets. First, we used an artificial dataset obtained from a model for the budding yeast cell cycle. The second data set is derived from experiments performed using HeLa cells. The results show that some interactions can be fully or, at least, partially determined under the Boolean model considered. Conclusions The algorithm proposed can be used as a first step for detection of gene/protein interactions. It is able to infer gene relationships from time-series data of gene expression, and this inference process can be aided by a priori knowledge available.